NILIMESH HALDER

Nilimesh Halder, PhD is an experienced applied Data Science and Machine Learning Specialist together with 14+ years of experiences. His specialisations are in Business Data Science & Forecasting as well as in Transcriptomics Data Science & Bioinformatics.

How to compare boosting ensemble Classifiers in Multiclass Classification

How to compare boosting ensemble Classifiers in Multiclass Classification     When it comes to classification tasks, there are many different machine learning models and techniques that can be used. Boosting ensemble classifiers are one popular method that can be used to improve the performance of a model. Boosting ensemble classifiers are a combination of …

How to add a Weight Regularization (l2) to a Deep Learning Model in Keras

    In deep learning, weight regularization is a technique used to prevent overfitting by adding a penalty term to the loss function. There are different types of weight regularization, but one of the most common is L2 regularization, also known as weight decay. L2 regularization adds a penalty term to the loss function that …

How to setup a Deep Learning Model in Keras

    Deep learning is a type of machine learning that uses neural networks with multiple layers, called deep neural networks, to analyze and understand complex data, such as images, speech, and text. In this essay, we will be discussing how to set up a deep learning model using Keras, a popular open-source library for …

Learn By Example 312 | How to setup a multiclass classification Deep Leaning Model in Keras?

How to setup a multiclass classification Deep Leaning Model in Keras?   A multiclass classification deep learning model is a type of machine learning model that is used to classify items into multiple categories or classes. For example, it can be used to classify images of handwritten digits into the numbers 0-9. In this essay, …

Learn By Example 311 | How to setup a binary classification Deep Leaning Model in Keras ?

How to setup a binary classification Deep Leaning Model in Keras     A binary classification deep learning model is a type of model that is trained to classify data into two distinct classes. In Keras, setting up a binary classification deep learning model involves a few steps. First, you will need to import the …

Learn By Example 310 | How to split train and test datasets using validation_split in Keras?

How to split train and test datasets using validation_split in Keras?   Splitting a dataset into a training and a test set is a crucial step when building a deep learning model. The training set is used to train the model and the test set is used to evaluate the model’s performance on unseen data. …

Applied Data Science Coding | Forecasting in Python | SARIMAX model | Air Quality Dataset

Applied Data Science Coding | Forecasting in Python | SARIMAX model | Air Quality Dataset   Data science is a field that uses various techniques to extract insights and knowledge from data. One important aspect of data science is forecasting, which involves using historical data to predict future events. Python is a popular programming language …

Time Series Forecasting in R – Auto ARIMA model using lynx dataset

Time Series Forecasting in R – Auto ARIMA model using lynx dataset   Auto ARIMA is a method for time series forecasting that automatically selects the best parameters for an ARIMA model, which stands for Auto-Regressive Integrated Moving Average. ARIMA models are a commonly used method for time series forecasting and are particularly well-suited for …